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Intracranial Aneurysm

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Integrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography.

Radiology. Artificial intelligence
Purpose To develop a deep learning model for the morphologic measurement of unruptured intracranial aneurysms (UIAs) based on CT angiography (CTA) data and validate its performance using a multicenter dataset. Materials and Methods In this retrospect...

Letter to Editor Regarding "Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience".

World neurosurgery
Artificial intelligence (AI) is increasingly significant in neurosurgery, enhancing differential diagnosis, preoperative evaluation, and surgical precision. A recent study in World Neurosurgery evaluated AI's role in aneurysm detection, comparing con...

Knowledge-Augmented Deep Learning for Segmenting and Detecting Cerebral Aneurysms With CT Angiography: A Multicenter Study.

Radiology
Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneur...

A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial aneurysms.

The British journal of radiology
OBJECTIVES: To investigate the usefulness of super-resolution deep learning reconstruction (SR-DLR) with cardiac option in the assessment of image quality in patients with stent-assisted coil embolization, coil embolization, and flow-diverting stent ...

Optimizing Coil Selection for Cerebral Aneurysm Treatment Using PyRadiomics and Machine Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study presents an innovative method to increase the accuracy of coil selection for treating cerebral aneurysms, leveraging advanced image analysis and machine learning models. We examined 273 cases of saccular cerebral aneurysms treated at The J...

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performan...

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

Neurosurgical focus
OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the c...

Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images.

Journal of digital imaging
The accuracy of computed tomography angiography (CTA) image interpretation depends on the radiologist. This study aims to develop a new method for automatically detecting intracranial aneurysms from CTA images using deep learning, based on a convolut...

Dense, deep learning-based intracranial aneurysm detection on TOF MRI using two-stage regularized U-Net.

Journal of neuroradiology = Journal de neuroradiologie
BACKGROUND AND PURPOSE: The prevalence of unruptured intracranial aneurysms in the general population is high and aneurysms are usually asymptomatic. Their diagnosis is often fortuitous on MRI and might be difficult and time consuming for the radiolo...

Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model.

Journal of neurointerventional surgery
BACKGROUND: Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.